Functional Relations, Random Coefficients, and Nonlinear Regression with Application to Kinetic Data (Lecture Notes in Statistics, 22). Questo articolo non è disponibile.Functional Relations, Random Coefficients, and Nonlinear Regression with Application to Kinetic Data (Lecture Notes in Statistics, 22)

The most important statistical concepts are the general linear model for Gaussian variables and the general methods of maximum likelihood estimation as well as the likelihood ratio test.

List of Contents.- 1. An example from physiology.- 1.1 The experiment and the data.- 1.2 The model.- 2. The general linear model.- 2.1 Independent observations with the same variance.- 2.2 Correlated observations with known covariance matrix.- 2.3 Correlated observations with unknown covariance matrix.- 2.4 The general linear model with estimated weights.- 3. The linear functional relation.- 3.1 Introduction.- 3.2 The model and the estimates.- 3.3 Comments on the model.- 3.4 Asymptotic theory.- 3.5 Asymptotic properties of the estimators.- 3.6 Asymptotic properties of the test statistics.- 3.7 Comments on the asymptotic results.- 4. Random coefficient models.- 4.1 Introduction.- 4.2 The balanced case.- 4.3 Test for the specification of the model.- 4.4 Test of hypotheses within the model.- 4.5 An analysis of the unbalanced case.- 5. Non linear regression.- 5.1 The model.- 5.2 Estimation.- 5.3 Hypothesis testing.- 5.4 Curvature.- 6. Some examples of non linear regression problems.- 7. References.- 8. Index.- Examples.- 9. Appendix.